NDLI: Frame recursive dynamic mean bias removal technique for robust environment-aware speech recognition in real world applications

Content Provider	IEEE Xplore Digital Library
Author	Chowdhury, M.F.R. Selouani, S.-A. O'Shaughnessy, D.
Copyright Year	2010
Description	Author affiliation: Dept. of Information Management, Université de Moncton, Shippagan, NB, Canada (Selouani, S.-A.) \|\| INRS - EMT, Université du Québec, Montréal, QC, Canada (Chowdhury, M.F.R.; O'Shaughnessy, D.)
Abstract	In this paper, we investigated and simulated the frame recursive dynamic mean bias removing technique in the cepstral domain with a time smoothing parameter in order to improve the robustness of automatic speech recognition (ASR) in realtime environments. The objective of this simulation was to examine the suitability of the frame recursive cepstral mean bias removal technique as a part of an effort to develop single channel joint additive noise and channel distortion compensation (JAC) algorithm in feature space for real-world applications. The Aurora2 speech corpus was used in this simulation. The simulation results show that the frame recursive dynamic mean bias removal technique performs better in real-time scenarios compared to conventional approaches (non real-time) to improve the robustness of ASR under noisy conditions.
Starting Page	1
Ending Page	5
File Size	152604
Page Count	5
File Format	PDF
ISBN	9781424453764
ISSN	08407789
DOI	10.1109/CCECE.2010.5575258
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-02
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems Speech recognition Hidden Markov models Speech Cepstral analysis Signal to noise ratio joint additive noise and channel distortion compensation Frame recursive bias removal robust speech recognition distributed speech recognition feature compensation
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

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